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Improved HIV case finding among key populations after differentiated data driven community testing approaches in Zambia

Author

Listed:
  • Joseph Kamanga
  • Kayla Stankevitz
  • Andres Martinez
  • Robert Chiegil
  • Lameck Nyirenda
  • Florence Mulenga
  • Mario Chen
  • Mulamuli Mpofu
  • Sam Lubasi
  • Moses Bateganya

Abstract

Introduction: Open Doors, an HIV prevention project targeting key populations in Zambia, recorded low HIV positivity rates (9%) among HIV testing clients, compared to national adult prevalence (12.3%), suggesting case finding efficiency could be improved. To close this gap, they undertook a series of targeted programmatic and management interventions. We share the outcomes of these interventions, specifically changes in testing volume, HIV positivity rate, and total numbers of key populations living with HIV identified. Methods: The project implemented a range of interventions to improve HIV case finding using a Total Quality Leadership and Accountability (TQLA) approach. We analyzed program data for key populations who received HIV testing six months before the interventions (October 2017–March 2018) and 12 months after (April 2018–March 2019). Interrupted time series analysis was used to evaluate the impact on HIV positivity and total case finding and trends in positivity and case finding over time, before and after the interventions. Results: While the monthly average number of HIV tests performed increased by only 14% post-intervention, the monthly average number of HIV positive individuals identified increased by 290%. The average HIV positivity rate rose from 9.7% to 32.4%. Positivity rates and case finding remained significantly higher in all post-intervention months. Similar trends were observed among FSW and MSM. Conclusions: The Open Doors project was able to reach large numbers of previously undiagnosed key populations by implementing a targeted managerial and technical intervention, resulting in a significant increase in the HIV positivity rate sustained over 12 months. These results demonstrate that differentiated, data-driven approaches can help close the 95-95-95 gaps among key populations.

Suggested Citation

  • Joseph Kamanga & Kayla Stankevitz & Andres Martinez & Robert Chiegil & Lameck Nyirenda & Florence Mulenga & Mario Chen & Mulamuli Mpofu & Sam Lubasi & Moses Bateganya, 2021. "Improved HIV case finding among key populations after differentiated data driven community testing approaches in Zambia," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-13, December.
    • Handle: RePEc:plo:pone00:0258573
    DOI: 10.1371/journal.pone.0258573
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    References listed on IDEAS

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    1. Kimbrough, L.W. & Fisher, H.E. & Jones, K.T. & Johnson, W. & Thadiparthi, S. & Dooley, S., 2009. "Accessing social networks with high rates of undiagnosed HIV infection: The social networks demonstration project," American Journal of Public Health, American Public Health Association, vol. 99(6), pages 1093-1099.
    2. Monisha Sharma & Roger Ying & Gillian Tarr & Ruanne Barnabas, 2015. "Systematic review and meta-analysis of community and facility-based HIV testing to address linkage to care gaps in sub-Saharan Africa," Nature, Nature, vol. 528(7580), pages 77-85, December.
    3. Ariel Linden, 2015. "Conducting interrupted time-series analysis for single- and multiple-group comparisons," Stata Journal, StataCorp LLC, vol. 15(2), pages 480-500, June.
    4. Ariel Linden, 2017. "A comprehensive set of postestimation measures to enrich interrupted time-series analysis," Stata Journal, StataCorp LLC, vol. 17(1), pages 73-88, March.
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